Mining authoritative and topical evidence from the blogosphere for improving opinion retrieval

• Published in: Information systems (Oxford) Vol. 78; pp. 199 - 213
• Main Authors: Huang, Jimmy Xiangji, He, Ben, Zhao, Jiashu
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2018; Elsevier Science Ltd
• Subjects: Blog retrieval; Blogs; Data mining; Information systems; Model matching; Neural matching model; Opinion mining; Retrieval; Sentiment analysis; Sentiment analysis; Opinion mining; Neural matching model; Blog retrieval
• ISSN: 0306-4379; 1873-6076
• DOI: 10.1016/j.is.2018.02.002

•We mine and utilize authoritative and topical evidence for improving the retrieval performance of opinionated blog posts.•We build a profile for each blogger and estimate the probability of topical words extracted from the training queries.•Further, a novel document-based neural matching mode is proposed to include different sources of information.•Our proposed approach does not use additional resources to extract opinion terms, which provides a new and promising avenue. The rise of the Internet blogging has created a highly dynamic Web society that involves bloggers’ views and opinions in response to real-world events. As an emerging research field, the blog post opinion retrieval requires finding not only relevant but also opinionated blog posts. Most of the current solutions are based on a dictionary of sentiment words for identifying subjective features from blog posts. In this paper, we propose to utilize novel evidence, namely the authoritative and topical evidence, for mining opinions from the blogosphere. We suggest that bloggers interested in controversial topics tend to express opinions in their posts, and therefore, it is beneficial to boost the ranking of blog posts written by such authors. We further improve our approach by extending with different sources of features, which is incorporated into a document-based neural matching model. Our experiments on the standard test data from the TREC 2006–2008 Blog track opinion finding task show that the proposed approach is capable of achieving remarkable improvements over strong baselines.